AI/ML
Easy and simple ML/DL model building and learning
Cloud-friendly environment for ML model development
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Benefits
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Cloud Native MLOps Environments
Supports Kubeflow, an open source MLOps platform built on Kubernetes. On Kubeflow, you can conveniently manage models and data or use various open source tools on a unified Kubeflow-native MLOps environment.
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Development Productivity Enhancement in Standardized Environment
Various machine learning frameworks from Tensorflow, Pytorch, Scikit-learn to Keras are supported on Kubeflow. Repetitive tasks across ML pipeline from model development, learning to deployment can be automated end-to-end, making it easier to create, configure, or re-use models.
Catalogs
Explore Samsung SDS cloud products
Kubernetes-based Machine Learning Platform
Automatically Extract Text and Data from Documents
Manages Champion Model by Recording and Comparing Experiment Information of AI model learning
Provides a Jupyter Notebook Environment to Construct Data Analysis Model
Manages the Learning and Execution History of AI Analytics Model in Pipeline
Provides IDE Workflow for Building and Learning Analysis Models
API Service that Understands and Analyzes the Meaning of Sentences/Texts
API Service that Recognizes and Analyzes Information from Images
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